Flow velocity tolerance of lowland stream caddisfly larvae (Trichoptera)

Brouwer, Jan H.F. de; Besse-Lototskaya, A.A.; Braak, Cajo J. F. ter; Kraak, Michiel H. S.; Verdonschot, P.F.M.

doi:10.1007/s00027-016-0507-y

Cited by 12 publications

(10 citation statements)

References 40 publications

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“…Giller et al 1991;Scrimgeour et al 1988;Robinson et al 2003). It is generally accepted that the effects of spates depend greatly on the taxon, as taxa have different resistance (ability to tolerate disturbance) and resilience to flow (ability to recover after a disturbance) (Death 2008;De Brouwer et al 2017). This study provided initial indication that the resistance to peak discharge of invertebrates not only depends on the taxon, but also varies between life stages.…”

Section: Discussionmentioning

confidence: 77%

Persist or perish: critical life stages determine the sensitivity of invertebrates to disturbances

et al. 2020

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A large proportion of studies assessing the impact of disturbances on the invertebrate community composition focus on a single life stage, assuming that those are an adequate indicator of environmental conditions. The effect of a specific disturbance may, however, depend on the life stage of the exposed organism. Therefore, we focused on the effect of spates on the caddisfly Agapetus fuscipes CURTIS (Trichoptera: Glossosomatidae) during different larval stages. A 2 year field study was performed in which we measured the discharge dynamics and population development of A. fuscipes in four lowland streams in The Netherlands. A stage-structured population model (i.e. StagePop) was used to test the impact of peak discharge on the different life stages, as larval instars 1-4 were not effectively sampled in the field. Four different mortality rates in response to spates were simulated, including a constant low, a constant high, a decreasing and an increasing impact per larval stage. This way, we were able to show a potential association between spates and population declines, where the stage-population model including decreasing impact by spates with increasing larval life stage most accurately described the population development of the larval instars 5-8. Focusing only on late instars could thus potentially result in underestimation of the effects of spates on this species. In conclusion, determination of responses of critical life stages to specific disturbances may help to identify the causes of the presence and absence of species, and thereby aid more effective management and restoration of degraded aquatic systems.

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Section: Discussionmentioning

confidence: 77%

Persist or perish: critical life stages determine the sensitivity of invertebrates to disturbances

et al. 2020

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“…As a result, 3 out of the 10 non-neutral loci (loci 56, 89, and 254) showed good model prediction performance (AUC > 0.7), whereas the other 7 non-neutral loci could not be well-modeled. The reason why we could not build a good model for the 7 non-neutral loci is probably because the natural selection on these loci was driven by the other environmental factors which were reported in other studies but not included in our analysis (e.g., velocity, chl-a) (Brouwer, Bessee-Lototskaya, ter Braak, Kraak, & Verdonschot, 2017;Li et al, 2016;Watanabe et al, 2014).…”

Section: Discussionmentioning

confidence: 99%

Machine‐learning‐based detection of adaptive divergence of the stream mayfly Ephemera strigata populations

Yaegashi

Carvajal

et al. 2020

Ecology and Evolution

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Adaptive divergence is a key mechanism shaping the genetic variation of natural populations. A central question linking ecology with evolutionary biology is how spatial environmental heterogeneity can lead to adaptive divergence among local populations within a species. In this study, using a genome scan approach to detect candidate loci under selection, we examined adaptive divergence of the stream mayfly Ephemera strigata in the Natori River Basin in northeastern Japan. We applied a new machine‐learning method (i.e., random forest) besides traditional distance‐based redundancy analysis (dbRDA) to examine relationships between environmental factors and adaptive divergence at non‐neutral loci. Spatial autocorrelation analysis based on neutral loci was employed to examine the dispersal ability of this species. We conclude the following: (a) E. strigata show altitudinal adaptive divergence among the populations in the Natori River Basin; (b) random forest showed higher resolution for detecting adaptive divergence than traditional statistical analysis; and (c) separating all markers into neutral and non‐neutral loci could provide full insight into parameters such as genetic diversity, local adaptation, and dispersal ability.

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“…This may be explained by natural selection at these seven loci being driven by environmental factors not included in our analysis (e.g. velocity and chlorophyll a) (Watanabe et al 2014, Li et al 2016, Brouwer et al 2017). RF is recommended for future studies including huge numbers of environmental variables to assess their effects on adaptive divergence because RF can perform well with large numbers of variables (Genuer et al 2010).…”

Section: Discussionmentioning

confidence: 99%

Detection of adaptive divergence in populations of the stream mayflyEphemera strigatawith machine learning

Li¹,

Yaegashi

Carvajal³

et al. 2018

Preprint

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1Adaptive divergence is a key mechanism shaping the genetic variation of natural populations. A central 1 2 question linking ecology with evolutionary biology concerns the role of environmental heterogeneity in 1 3 determining adaptive divergence among local populations within a species. In this study, we examined 1 4 adaptive the divergence among populations of the stream mayfly Ephemera strigata in the Natori River 1 5Basin in northeastern Japan. We used a genome scanning approach to detect candidate loci under 1 6 selection and then applied a machine learning method (i.e. Random Forest) and traditional distance-1 7 based redundancy analysis (dbRDA) to examine relationships between environmental factors and 1 8 adaptive divergence at non-neutral loci. We also assessed spatial autocorrelation at neutral loci to 1 9 quantify the dispersal ability of E. strigata. Our main findings were as follows: 1) random forest shows a 2 0 higher resolution than traditional statistical analysis for detecting adaptive divergence; 2) separating 2 1 markers into neutral and non-neutral loci provides insights into genetic diversity, local adaptation and 2 2 dispersal ability and 3) E. strigata shows altitudinal adaptive divergence among the populations in the 2 3 Natori River Basin.2 4

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Flow velocity tolerance of lowland stream caddisfly larvae (Trichoptera)

Cited by 12 publications

References 40 publications

Persist or perish: critical life stages determine the sensitivity of invertebrates to disturbances

Persist or perish: critical life stages determine the sensitivity of invertebrates to disturbances

Machine‐learning‐based detection of adaptive divergence of the stream mayfly Ephemera strigata populations

Detection of adaptive divergence in populations of the stream mayflyEphemera strigatawith machine learning

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